Enthought
Scientific Software Developer

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Job Title: Scientific Software Developer
We are hiring a Scientific Software Developer to join our client-facing solution delivery team. Working agent-first, you will pair deep scientific expertise with agentic AI coding tools to move from research question to working software — building data-driven models, AI-based decision-support tools, and analysis pipelines for the world’s leading R&D organizations.
Key Responsibilities
- Design end-to-end scientific solutions — apply deep knowledge of statistics, optimization, machine learning, and related areas to translate client R&D problems into architectures spanning data, models, and user-facing applications.
- Work agent-first — use AI coding assistants and autonomous coding agents as your default way to explore data, prototype models, build software, write tests, and produce documentation, compressing the path from research question to working solution.
- Direct AI agents like a technical lead — decompose scientific and engineering problems into well-scoped tasks, give agents the domain context and scientific constraints they need, and iterate toward correct, defensible results.
- Solve complex research and product-development problems in close collaboration with client researchers and business leaders.
- Build data-driven models, AI-based decision-support tools, and automated analysis pipelines, and assemble them into web-based solutions involving GUIs, 2D and 3D graphics, and cloud computing.
- Design AI-enabled and agentic capabilities into client solutions where they add value — held to the same rigor as any other component.
- Apply judgment about where AI and generative approaches fit and where they don’t, balancing speed against reliability and reproducibility.
- Take part in collaborative development practices — code review, architecture reviews, sprint planning, retrospectives, and daily standups — and interface directly with clients to define, demonstrate, and refine solutions.
- Handle client data and intellectual property responsibly, using AI tools only in approved, secure configurations.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
What We Offer
- Meaningful impact — your work directly advances scientific breakthroughs, from accelerating drug discovery to developing sustainable materials.
- A front-row seat to agentic AI — work at an automation-first company where every role directs AI tools, and help define how the industry puts them to work.
- World-class colleagues — collaborate with some of the smartest, kindest scientists and engineers around.
- Continuous learning — access to Enthought’s training programs in Python, machine learning, and scientific computing.
- A global, collaborative culture across our Cambridge, Austin, and Tokyo offices.
- Flexible hybrid work based out of our Cambridge office.
- Competitive compensation and benefits.


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Who Thrives Here
Everyone at Enthought shares a common set of traits: exceptional integrity, analytic intelligence, a sense of urgency, the ability to simplify the complex, openness in communication, empathy for people, and endurance. If you are endlessly curious, take full ownership of your work, and are excited to help shape how science gets done in the era of agentic AI, you will feel at home here.
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